A study led by researchers from IDIAPJGol shows that the use of artificial intelligence in primary care combined with geospatial data and preconception information can improve the prediction of health problems in children.

The authors, Elena Segundo, Jordi Carrere-Molina, María Aragón and Roger Mallol-Parera, point out that this integration would allow health professionals to anticipate risks, such as chronic diseases or respiratory disorders, and intervene before pregnancy. These results could have a major impact on preventive care and the personalization of care in the primary care network. The authors state that “in the long term, we support the idea that geospatial health may play an increasingly relevant role in research and in public health policy and precision medicine.”

The article argues for the importance of including the mother’s geographic history in medical records, which would provide health professionals with valuable information about environmental and socioeconomic factors that can affect child health. This would represent a step forward for preventive medicine and the personalization of long-term treatments.

Predictive models

The study was based on the use of data from the Information System for the Development of Primary Care (SIDIAP), which collects health information from more than six million patients in Catalonia. These data, combined with data mining and AI techniques, have been key to developing predictive models that could transform the way health is managed in primary care.

Article reference

Segundo E, Carrere-Molina J, Aragón M, Mallol-Parera R. Advancing geospatial preconception health research in primary care through medical informatics and artificial intelligence. Health Place. 2024 Sep;89:103337. doi: 10.1016/j.healthplace.2024.103337. Epub 2024 Aug 15. PMID: 39151214.